# 學生對 杜克大学 提供的 Data Science Math Skills 的評價和反饋

4.5
stars
2,199 個評分
490 條評論

## 課程概述

Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time. Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to more advanced material. Topics include: ~Set theory, including Venn diagrams ~Properties of the real number line ~Interval notation and algebra with inequalities ~Uses for summation and Sigma notation ~Math on the Cartesian (x,y) plane, slope and distance formulas ~Graphing and describing functions and their inverses on the x-y plane, ~The concept of instantaneous rate of change and tangent lines to a curve ~Exponents, logarithms, and the natural log function. ~Probability theory, including Bayes’ theorem. While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization. Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel." Good luck and we hope you enjoy the course!...

## 熱門審閱

##### AS

Jan 12, 2019

Effective way to refresh and add the Data Science math skills! Thanks a lot! At the time of the study some of the quizzes content were not rendering correctly on mobile devices (both iPad and Android)

##### PS

Jul 23, 2017

This is neat little course to revise math fundamentals. I generally find learning probability a little tricky. This course helped me a lot in better understanding Bayes Theorem. Thank you professors.

## 426 - Data Science Math Skills 的 450 個評論（共 482 個）

May 06, 2017

I definitely learned a lot in this course, and, as someone who has historically avoided mathematics, I think it is a fairly good introduction to these concepts for people at my level. However, I think the course was somewhat inconsistent. The final module could really use some more explanation and examples. Probability is a very abstract field, and it can be difficult to take real world examples and translate them into formulas. I think that the module would benefit greatly from spending some extra time on translating english-language situations into formulas. There were also some non-trivial errors in the videos that need to be corrected. Overall, I'm pretty happy with the course but I think it doesn't yet fill out its potential.

Oct 05, 2019

The first part of this course was great. It was the right level of material, taught simply and effectively with quizzes and exams that were on par with the taught material. The second half was not so great. The teaching style of the second teacher did not convey the material as effectively as the first teacher. Also, I felt that the week 4 probability quiz and final exam had material way beyond what was taught during the lesson. There should have been some exercises to warm us up and get us to the difficulty level of the final. It felt like going from 0-100 mph. Overall because of the stark difference in teaching and difficulty of the final exam of part 4, I can only give this course three stars for the great start.

Nov 12, 2018

The course started nice and well explained, there are some useful info missing, e.g. what is Euler's constant and why is it defined as it is and then more practice examples would be also welcome. All that would be fine and I would have given the course full 5 stars, but I felt really discouraged with so many errors in the practice quizes and even in the last graded quiz. Additionally, it was a bit annoying that I could not finish the quiz on my phone as in one of the questions there was only the problem and the possible answers visible, not the question itself.

Sep 23, 2017

If you are familiar with the concepts in this course, it will be fine. If, however, you happen to discover them for the first time here, the instructors go so quickly in their explanations that you'll end up with a high level of frustration.

When it comes to statistics, fewer concepts introduced per video, and more examples of each concepts would have been a better approach for real beginners.

Finally, don't believe you've acquired the "math skills" necessary for data science just by following this course. In this, the title can be seriously misleading.

Jan 26, 2018

This course was a good refresher to some important math concepts needed for further study of statistics and data science. Most of the modules and videos were clear and easy to follow. However, I found the module on probability to be confusing and overly complex in its structure and explanations. For those with stronger math skills than me, it's probably a fairly easy course. I found it appropriately challenging, and for the most part it built my confidence in this important area.

Jan 31, 2018

The course should be a guide text with very detail readings, with a lot of solved examples (complex ones) step by step. The readings should also explain very weel what I'm doing and why I'm doing each step, and in the end explain the exercise as a whole.

The practice quizzes should bring very real life examples (as thouse of VBS tests) and they have to match de guide text.

The videos should be made only from the most comum doubts and mistakes in the practice quizzes.

Feb 25, 2018

The first two weeks were well paced, in week 3 I think too much is covered too quickly and in week 4 there is a further acceleration. That said, the course was good in highlighting the areas that I feel I need to work on and motivated me to take University of Zurich's intro to probability which filled the gap for the content from week 4 here. I think this might be a good refresher course for someone whose knowledge is not too stale.

Feb 18, 2019

good subject matter choice; however, quality varied between the two professors. weeks 1-3 provided good clear lectures and enough practice questions; but week 4 had several confusing points in the lecture, then not enough practice. I really had to supplement my learning with outside videos and problems for week 4. but i passed the final test first time. thanks for narrowing down the maths needed for data science.

Sep 21, 2019

Keep in mind that this is meant to be an introduction to some of the math topics used in data science, it is not a comprehensive course. The course needs to include worksheets with practice problems for the students to practice. The instructors do not use enough real-world examples to demonstrate how the theory is applied.

Jun 22, 2019

Felt like the first 3 weeks were pretty good but the probability section needs a lot more detailed explanations and examples to make the information clear. For those that are already OK with this subject, it's probably fine but for those that haven't had much background in probability, this part was lacking.

Jan 17, 2018

First 2 weeks of the course is amazing, very good didactics. The second teacher does not use very good examples, and the thing starts to fill like old math classes, but overall is good. I will need to redo the last 2 weeks because i fill that I will not remember most of it so easy as the first 2 weeks.

May 27, 2018

Good for high level understanding of few of the concepts. But last week 4 tutorials are covered at very high level , it was quite difficult to understand probability topic without referring to other online tutorials. I wish more examples could be given in the tutorials to strengthen understanding.

Jul 25, 2017

The class is good. However, the second half of the class zips through concepts that need a lot more explanation than is provided. Moreover this class would benefit from an optional tutorial on how to input factorials into a calculator as the answers on the exam go to the 8th decimal place.

Nov 08, 2019

You guys need to give better practice examples and scenarios in Weeks 3 and 4. That being said, I think the courses you presented give a nice foundation. I'm going to practice on my own time finding problems of the subjects you've spoken about.

Dec 22, 2017

A good review of basic math skills, however I believed the "SUM RULE, CONDITIONAL PROBABILITY AND BAYES'THEOREM should be discussed much more in the last week module with more example and exercise. The 1,2,3 week are great.

Oct 18, 2017

I feel the probability portion of the course was too quick for the material covered. Yet the quizzes for the probability section were very demanding. It was difficult to successfully complete the probability quizzes.

Aug 27, 2017

Broad coverage of topics in a compact course. Useful for those looking for a refresher course. Could be improved by explaining where in data science the chosen topics would be relevant to provide context.

Feb 03, 2018

the course was really good. I just hope that we can get more practice questions in between the lectures so that we can understand the concept more precisely and deeply.

Jan 20, 2019

Overall it's a good one. In Math part I liked it a lot but in Stat I think Prof should explain a bit more in depth and the content is not good enough.

Feb 07, 2019

The material covered was very useful for a beginner/intermediate course, however, the style of the presenters was not always very clear.

Dec 13, 2017

it's the foundation for data science, but these contents are too simple. I think it's not enough for a good data analyst.

May 29, 2017

a good selection of topics, but way too formula based rather than understanding based, especially in the second half.

Sep 26, 2019

The last module could have been done better. More examples to be included for explaining probability problems.

Aug 30, 2017

Basics knowledge, i liked first part about functions, but second was not quite good for me.

Feb 10, 2017

The Probability section could use more practical examples, I found it difficult to follow.